Increasingly, large amounts of data originate from networks of sensors and devices. Query processing and data analytics platforms can analyze the data organized in time order to derive insights from the data. However, due to network delays, intermittent machine failures, and race conditions, events can be received out-of-order compared to the time order of when the events were created. Further, processing these out-of-order streams of data presents tradeoffs between latency, throughput, accuracy, and memory usage.